Sentence examples for binary and continuous covariates from inspiring English sources

The graph is separated to display odds ratios for both binary and continuous covariates.

Both categorical and continuous covariates can be used.

This resampling study identified that standard MI methods for handling missing covariate data can be adequately used in prognostic modelling studies where the outcome is survival time with up to 50% MAR missingness within binary or continuous covariates with moderate skewness.

Figure 3 presents the empirical type I error rates for both the binary and continuous traits, with or without covariate effects.

We estimated disease odds using GAMs, a form of nonparametric or semiparametric regression with the ability to analyze binary and continuous outcome data while adjusting for covariates (Hastie and Tibshirani 1990; Kelsall and Diggle 1998; Webster et al. 2006).

We estimated local disease odds using generalized additive models, a form of non-parametric or semi-parametric regression with the ability to analyze binary and continuous outcome data while adjusting for covariates [ 13, 18].

We consider binary covariate, continuous covariate (time covariate), and an interaction between binary and time covariate along with the usual intercept term.

Power of the methods also was evaluated for binary and continuous traits under the single locus alternative model, with or without covariate effects.

Cost vectors associated with binary and continuous variables.

Both binary and continuous traits were simulated.

Our methodology only requires summary statistics and is able to handle both binary and continuous traits.